William R. Wieder

Relationships among net primary productivity, nutrients and climate in tropical rain forest: a pan-tropical analysis

Tropical rain forests play a dominant role in global biosphere-atmosphere CO(2) exchange. Although climate and nutrient availability regulate net primary production (NPP) and decomposition in all terrestrial ecosystems, the nature and extent of such controls in tropical forests remain poorly resolved. We conducted a meta-analysis of carbon-nutrient-climate relationships in 113 sites across the tropical forest biome. Our analyses showed that mean annual temperature was the strongest predictor of aboveground NPP (ANPP) across all tropical forests, but this relationship was driven by distinct temperature differences between upland and lowland forests. Within lowland forests (< 1000 m), a regression tree analysis revealed that foliar and soil-based measurements of phosphorus (P) were the only variables that explained a significant proportion of the variation in ANPP, although the relationships were weak. However, foliar P, foliar nitrogen (N), litter decomposition rate (k), soil N and soil respiration were all directly related with total surface (0-10 cm) soil P concentrations. Our analysis provides some evidence that P availability regulates NPP and other ecosystem processes in lowland tropical forests, but more importantly, underscores the need for a series of large-scale nutrient manipulations - especially in lowland forests - to elucidate the most important nutrient interactions and controls.

Quantifying global soil carbon losses in response to warming

The majority of the Earth’s terrestrial carbon is stored in the soil. If anthropogenic warming stimulates the loss of this carbon to the atmosphere, it could drive further planetary warming. Despite evidence that warming enhances carbon fluxes to and from the soil, the net global balance between these responses remains uncertain. Here we present a comprehensive analysis of warming-induced changes in soil carbon stocks by assembling data from 49 field experiments located across North America, Europe and Asia. We find that the effects of warming are contingent on the size of the initial soil carbon stock, with considerable losses occurring in high-latitude areas. By extrapolating this empirical relationship to the global scale, we provide estimates of soil carbon sensitivity to warming that may help to constrain Earth system model projections. Our empirical relationship suggests that global soil carbon stocks in the upper soil horizons will fall by 30 ± 30 petagrams of carbon to 203 ± 161 petagrams of carbon under one degree of warming, depending on the rate at which the effects of warming are realized. Under the conservative assumption that the response of soil carbon to warming occurs within a year, a business-as-usual climate scenario would drive the loss of 55 ± 50 petagrams of carbon from the upper soil horizons by 2050. This value is around 12–17 per cent of the expected anthropogenic emissions over this period. Despite the considerable uncertainty in our estimates, the direction of the global soil carbon response is consistent across all scenarios. This provides strong empirical support for the idea that rising temperatures will stimulate the net loss of soil carbon to the atmosphere, driving a positive land carbon–climate feedback that could accelerate climate change.

Controls over leaf litter decomposition in wet tropical forests

Tropical forests play a substantial role in the global carbon (C) cycle and are projected to experience significant changes in climate, highlighting the importance of understanding the factors that control organic matter decomposition in this biome. In the tropics, high temperature and rainfall lead to some of the highest rates of litter decomposition on earth, and given the near-optimal abiotic conditions, litter quality likely exerts disproportionate control over litter decomposition. Yet interactions between litter quality and abiotic variables, most notably precipitation, remain poorly resolved, especially for the wetter end of the tropical forest biome. We assessed the importance of variation in litter chemistry and precipitation in a lowland tropical rain forest in southwest Costa Rica that receives >5000 mm of precipitation per year, using litter from 11 different canopy tree species in conjunction with a throughfall manipulation experiment. In general, despite the exceptionally high rainfall in this forest, simulated throughfall reductions consistently suppressed rates of litter decomposition. Overall, variation between species was greater than that induced by manipulating throughfall and was best explained by initial litter solubility and lignin:P ratios. Collectively, these results support a model of litter decomposition in which mass loss rates are positively correlated with rainfall up to very high rates of mean annual precipitation and highlight the importance of phosphorus availability in controlling microbial processes in many lowland tropical forests.

Toward more realistic projections of soil carbon dynamics by Earth system models

Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.

Experimental drought in a tropical rain forest increases soil carbon dioxide losses to the atmosphere

Climate models predict precipitation changes for much of the humid tropics, yet few studies have investigated the potential consequences of drought on soil carbon (C) cycling in this important biome. In wet tropical forests, drought could stimulate soil respiration via overall reductions in soil anoxia, but previous research suggests that litter decomposition is positively correlated with high rainfall fluxes that move large quantities of dissolved organic matter (DOM) from the litter layer to the soil surface. Thus, reduced rainfall could also limit C delivery to the soil surface, reducing respiration rates. We conducted a throughfall manipulation experiment to investigate how 25% and 50% reductions in rainfall altered both C movement into soils and the effects of those DOM fluxes on soil respiration rates. In response to the experimental drought, soil respiration rates increased in both the -25% and -50% treatments. Throughfall fluxes were reduced by 26% and 55% in the -25% and -50% treatments, respectively. However, total DOM fluxes leached from the litter did not vary between treatments, because the concentrations of leached DOM reaching the soil surface increased in response to the simulated drought. Annual DOM concentrations averaged 7.7 +/- 0.8, 11.2 +/- 0.9, and 15.8 +/- 1.2 mg C/L in the control, -25%, and -50% plots, respectively, and DOM concentrations were positively correlated with soil respiration rates. A laboratory incubation experiment confirmed the potential importance of DOM concentration on soil respiration rates, suggesting that this mechanism could contribute to the increase in CO2 fluxes observed in the reduced rainfall plots. Across all plots, the data suggested that soil CO2 fluxes were partially regulated by the magnitude and concentration of soluble C delivered to the soil, but also by soil moisture and soil oxygen availability. Together, our data suggest that declines in precipitation in tropical rain forests could drive higher CO2 fluxes to the atmosphere both via increased soil 02 availability and through responses to elevated DOM concentrations.

Evaluating litter decomposition in earth system models with long-term litterbag experiments: an example using the Community Land Model version 4 (CLM4)

Decomposition is a large term in the global carbon budget, but models of the earth system that simulate carbon cycle-climate feedbacks are largely untested with respect to litter decomposition. We tested the litter decomposition parameterization of the community land model version 4 (CLM4), the terrestrial component of the community earth system model, with data from the long-term intersite decomposition experiment team (LIDET). The LIDET dataset is a 10-year study of litter decomposition at multiple sites across North America and Central America. We performed 10-year litter decomposition simulations comparable with LIDET for 9 litter types and 20 sites in tundra, grassland, and boreal, conifer, deciduous, and tropical forest biomes using the LIDET-provided climatic decomposition index to constrain temperature and moisture effects on decomposition. We performed additional simulations with DAYCENT, a version of the CENTURY model, to ask how well an established ecosystem model matches the observations. The results show large discrepancy between the laboratory microcosm studies used to parameterize the CLM4 litter decomposition and the LIDET field study. Simulated carbon loss is more rapid than the observations across all sites, and nitrogen immobilization is biased high. Closer agreement with the observations requires much lower decomposition rates, obtained with the assumption that soil mineral nitrogen severely limits decomposition. DAYCENT better replicates the observations, for both carbon mass remaining and nitrogen, independent of nitrogen limitation. CLM4 has low soil carbon in global earth system simulations. These results suggest that this bias arises, in part, from too rapid litter decomposition. More broadly, the terrestrial biogeochemistry of earth system models must be critically tested with observations, and the consequences of particular model choices must be documented. Long-term litter decomposition experiments such as LIDET provide a real-world process-oriented benchmark to evaluate models.

Understanding the dominant controls on litter decomposition

Summary 1. Litter decomposition is a biogeochemical process fundamental to element cycling within ecosystems, influencing plant productivity, species composition and carbon storage. 2. Climate has long been considered the primary broad-scale control on litter decomposition rates, yet recent work suggests that plant litter traits may predominate. Both decomposition paradigms, however, rely on inferences from cross-biome litter decomposition studies that analyse site-level means. 3. We re-analyse data from a classical cross-biome study to demonstrate that previous research may falsely inflate the regulatory role of climate on decomposition and mask the influence of unmeasured local-scale factors. 4. Using the re-analysis as a platform, we advocate experimental designs of litter decomposition studies that involve high within-site replication, measurements of regulatory factors and processes at the same local spatial grain, analysis of individual observations and biome-scale gradients. 5. Synthesis. We question the assumption that climate is the predominant regulator of decomposition rates at broad spatial scales. We propose a framework for a new generation of studies focused on factoring local-scale variation into the measurement and analysis of soil processes across broad scales. Such efforts may suggest a revised decomposition paradigm and ultimately improve confidence in the structure, parameter estimates and hence projections of biogeochemical models.

Explicitly representing soil microbial processes in Earth system models

©2015. American Geophysical Union. All Rights Reserved. Microbes influence soil organic matter decomposition and the long-term stabilization of carbon (C) in soils. We contend that by revising the representation of microbial processes and their interactions with the physicochemical soil environment, Earth system models (ESMs) will make more realistic global C cycle projections. Explicit representation of microbial processes presents considerable challenges due to the scale at which these processes occur. Thus, applying microbial theory in ESMs requires a framework to link micro-scale process-level understanding and measurements to macro-scale models used to make decadal- to century-long projections. Here we review the diversity, advantages, and pitfalls of simulating soil biogeochemical cycles using microbial-explicit modeling approaches. We present a roadmap for how to begin building, applying, and evaluating reliable microbial-explicit model formulations that can be applied in ESMs. Drawing from experience with traditional decomposition models, we suggest the following: (1) guidelines for common model parameters and output that can facilitate future model intercomparisons; (2) development of benchmarking and model-data integration frameworks that can be used to effectively guide, inform, and evaluate model parameterizations with data from well-curated repositories; and (3) the application of scaling methods to integrate microbial-explicit soil biogeochemistry modules within ESMs. With contributions across scientific disciplines, we feel this roadmap can advance our fundamental understanding of soil biogeochemical dynamics and more realistically project likely soil C response to environmental change at global scales.

A comparison of plot‐based satellite and Earth system model estimates of tropical forest net primary production

Net primary production (NPP) by plants represents the largest annual flux of carbon dioxide (CO2) from the atmosphere to the terrestrial biosphere, playing a critical role in the global carbon (C) cycle and the Earths climate. Rates of NPP in tropical forests are thought to be among the highest on Earth, but debates about the magnitude, patterns, and controls of NPP in the tropics highlight uncertainty in our understanding of how tropical forests may respond to environmental change. Here, we compared tropical NPP estimates generated using three common approaches: (1) field-based methods scaled from plot-level measurements of plant biomass, (2) radiation-based methods that model NPP from satellite-derived radiation absorption by plants, (3) and biogeochemical model-based methods. For undisturbed tropical forests as a whole, the three methods produced similar NPP estimates (i.e., ~ 10 Pg C yr−1). However, the three different approaches produced vastly different patterns of NPP both in space and through time, suggesting that our understanding of tropical NPP is poor and that our ability to predict the response of NPP in the tropics to environmental change is limited. To address this shortcoming, we suggest the development of an expanded, high-density, permanent network of sites where NPP is continuously evaluated using multiple approaches. Well-designed NPP megatransects that include a high-density plot network would significantly increase the accuracy and certainty in the observed rates and patterns of tropical NPP and improve the reliability of Earth system models used to predict NPP–carbon cycle–climate interactions into the future.

Evaluating soil biogeochemistry parameterizations in Earth system models with observations

Soils contain large reservoirs of terrestrial carbon (C), yet soil C dynamics simulated in Earth systems models show little agreement with each other or with observational data sets. This uncertainty underscores the need to develop a framework to more thoroughly evaluate model parameterizations, structures, and projections. Toward this end we used an analytical solution to calculate approximate equilibrium soil C pools for the Community Land Model version 4 (CLM4cn) and Daily Century (DAYCENT) soil biogeochemistry models. Neither model generated sufficient soil C pools when forced with litterfall inputs from CLM4cn; however, global totals and spatial correlations of soil C pools for both models improved when calculated with litterfall inputs derived from observational data. DAYCENT required additional modifications to simulate soil C pools in deeper soils (0–100 cm). Our best simulations produced global soil C pools totaling 746 and 978 Pg C for CLM4cn and DAYCENT parameterizations, respectively, compared to observational estimates of 1259 Pg C. In spite of their differences in complexity and equilibrium soil C pools, predictions of soil C losses with warming temperatures through 2100 were strikingly similar for both models. Ultimately, CLM4cn and DAYCENT come from the same class of models that represent the turnover of soil C as a first-order decay process. While this approach may have utility in calculating steady state soil C pools, the applicability of this model configuration in transient simulations remains poorly evaluated.